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. 2023 Apr 7:14:1110396.
doi: 10.3389/fgene.2023.1110396. eCollection 2023.

Potential effective diagnostic biomarker in patients with primary and metastatic small intestinal neuroendocrine tumors

Jianxian Chen  1 , Yiliang Meng  1 , Xiaojuan Huang  1 , Xuegan Liao  1 , Xiaochun Tang  1 , Yuanchao Xu  1 , Jie Li  1
Affiliations

Potential effective diagnostic biomarker in patients with primary and metastatic small intestinal neuroendocrine tumors

Jianxian Chen et al. Front Genet. .

Abstract

Background: Small intestinal neuroendocrine tumors (SI-NETs) are the most common malignant tumors of the small intestine, with many patients presenting with metastases and their incidence increasing. We aimed to find effective diagnostic biomarkers for patients with primary and metastatic SI-NETs that could be applied for clinical diagnosis. Methods: We downloaded GSE65286 (training set) and GSE98894 (test set) from the GEO database and performed differential gene expression analysis to obtain differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs). The functions and pathways involved in these genes were further explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a global regulatory network involving dysregulated genes in SI-NETs was constructed based on RNAInter and TRRUST v2 databases, and the diagnostic power of hub genes was identified by receiver operating characteristic curve (ROC). Results: A total of 2,969 DEGs and DElncRNAs were obtained in the training set. Enrichment analysis revealed that biological processes (BPs) and KEGG pathways were mainly associated with cancer. Based on gene set enrichment analysis (GSEA), we obtained five BPs (cytokinesis, iron ion homeostasis, mucopolysaccharide metabolic process, platelet degranulation and triglyceride metabolic process) and one KEGG pathway (ppar signaling pathway). In addition, the core set of dysregulated genes obtained included MYL9, ITGV8, FGF2, FZD7, and FLNC. The hub genes were upregulated in patients with primary SI-NETs compared to patients with metastatic SI-NETs, which is consistent with the training set. Significantly, the results of ROC analysis showed that the diagnostic power of the hub genes was strong in both the training and test sets. Conclusion: In summary, we constructed a global regulatory network in SI-NETs. In addition, we obtained the hub genes including MYL9, ITGV8, FGF2, FZD7, and FLNC, which may be useful for the diagnosis of patients with primary and metastatic SI-NETs.

Keywords: hub genes; intestinal neuroendocrine tumor; lncRNA; metastatic small intestinal neuroendocrine rumors; primary small intestinal neuroendocrine tumor.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The workflow of this study.
FIGURE 2
FIGURE 2
Expression disorders of SI-NETs. (A) Manhattan plot for DEGs and DElncRNA. The three most significantly DEGs and DElncRNA are marker and labeled with their names. (B) Hierarchical clustering dendrograms of the expression patterns of DEGs that distinguish between patients with primary and metastatic SI-NETs. (C) Hierarchical clustering dendrograms of the expression patterns of DElnRNA that distinguish between patients with primary and metastatic SI-NETs. DEGs: differentially expressed genes, DElncRNA: differentially expressed lncRNA, SI-NETs: small intestine neuroendocrine tumors. (D) Infiltration of immune cells between primary and metastatic SI-NETs.
FIGURE 3
FIGURE 3
Biological processes and pathways of DEGs for patients with SI-NETs. (A) The top 20 biological processes for patients with SI-NETs. (B) The top 20 KEGG pathways for patients with SI-NETs. (C) GSEA results revealed the significantly enriched GO-BPs between patients with primary and metastatic SI-NETs. (D) GSEA results revealed the significantly enriched KEGG pathways between patients with primary and metastatic SI-NETs. (E) The ClueGo network for GO-BPs in patients with SI-NETs. (F) The ClueGO network for KEGG pathways in patients with SI-NETs. SI-NETs, small intestine neuroendocrine tumors; GSEA, gene set enrichment analysis; GO, gene ontology; BPs, biological processes; KEGG, Kyoto Encyclopedia of Genes and Genomes.
FIGURE 4
FIGURE 4
The global regulatory landscape in SI-NETs. (A) Sankey plot: Graphical summary of lncRNA regulating KEGG pathways through mRNA. (B) Sankey plot: Graphical summary of TFs regulating KEGG pathways through mRNA. (C) Molecular docking model: The prediction of targeted binding FGF2 and WWTR1/PGR/MITF, FLNC and MITF/PGR, as well as FZD7 and MITF. (D) The global regulatory landscape SI-NETs: lncRNA/TFs-mRNA-KEGG pathways network. (E) 3 KEGG pathways for further study. Node maps degree value. Light purple represents a smaller degree value, while dark purple representing a larger degree value. Degree value represents the number of genes interacting with other genes. SI-NETs, small intestine neuroendocrine tumors; KEGG, Kyoto Encyclopedia of Genes and Genomes; TFs, transcription factors.
FIGURE 5
FIGURE 5
The identification of diagnostic power of the hub genes in SI-NETs. (A) The heatmap for the hub genes in GSE65286. (B) Circo plot: The expression level of the hub genes in GSE65286 and GSE98894. (C) The ROC analysis for the hub genes in GSE65286 and GSE98894. (D) The hub genes are significantly involved in biological processes. (E) The hub genes are significantly involved in the KEGG signaling pathway. SI-NETs, small intestine neuroendocrine tumors; ROC, receiver operator characteristic.
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